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Cerebral laterality, via hemispheric specialisation, has been evidenced across the animal kingdom and linked to cognitive performance in a number of species. Previously it has been suggested that cognitive processing is more efficient in brains with stronger hemispheric differences in processing, which may be the key fitness benefit driving the evolution of laterality. However, evidence supporting a positive association between cognitive performance and lateralization is mixed: data from studies of fish and birds show a positive relationship whereas more limited data from studies of mammals suggest a weak or even negative relationship, suggesting the intriguing possibility of a mammal/non-mammal divide in the nature of this relationship. Here, we report an empirical test examining the relationship between lateralization and cognitive performance in wild grey squirrels (Sciurus carolinensis) by measuring left/right paw preference as a behavioural assay of cerebral lateralization and learning speed as an assay of cognitive efficiency. We carried out a motor-based laterality test using a reaching paradigm and measured learning speed on a problem-solving task. In accordance with the suggestion of a mammal/non-mammal divide, we found a negative relationship between strength of paw preference and performance on the learning task. We discuss this finding in light of niche-specific adaptations, task-specific demands and cognitive flexibility.

Behavioral ecologists have long been comfortable assuming that genetic architecture does not constrain which phenotypescan evolve (the “phenotypic gambit”). For flexible behavioral traits, however, solutions to adaptive problems are reached not only by genetic evolution but also by behavioral changes within an individual’s lifetime, via psychological mechanisms such as learning. Standard optimality approaches ignore these mechanisms, implicitly assuming that they do not constrain the expression of adaptive behavior. This assumption, which we dub the behavioral gambit, is sometimes wrong: evolved psychological mechanisms can prevent animals from behaving optimally in specific situations. To understand the functional basis of behavior, we would do better by considering the underlying mechanisms, rather than the behavioral outcomes they produce, as the target of selection. This change of focus yields new, testable predictions about evolutionary equilibria, the development of behavior, and the properties of cognitive systems. Studies on the evolution of learning rules hint at the potential insights to be gained, but such mechanism-based approaches are underexploited. We highlight three future research priorities: (1) systematic theoretical analysis of the evolutionary properties of learning rules; (2) detailed empirical study of how animals learn in nonforaging contexts;and (3) analysis of individual differences in learning rules and their associated fitness consequences. [ABSTRACT FROM PUBLISHER]

An introduction to the journal is presented in which the author discusses decision making in organisms and animals.